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The Performativity of AI-powered Event Detection: How AI Creates a Racialized Protest and Why Looking for Bias Is Not a Solution
In: Science, technology, & human values: ST&HV, Band 49, Heft 5, S. 1045-1072
ISSN: 1552-8251
This article builds a theoretical framework with which to confront the racializing capabilities of artificial intelligence (AI)-powered real-time Event Detection and Alert Creation (EDAC) software when used for protest detection. It is well-known that many AI-powered systems exacerbate social inequalities by racializing certain groups and individuals. We propose the feminist concept of performativity, as defined by Judith Butler and Karen Barad, as a more comprehensive way to expose and contest the harms wrought by EDAC than that of other "de-biasing" mechanisms. Our use of performativity differs from and complements other Social Studies of Science and Technology (STS) work because of its rigorous approach to how iterative, citational, and material practices produce the effect of race. We focus on Geofeedia and Dataminr, two EDAC companies that claim to be able to "predict" and "recognize" the emergence of dangerous protests, and show how their EDAC tools performatively produce the phenomena which they are supposed to observe. Specifically, we argue that this occurs because these companies and their stakeholders dictate the thresholds of (un)intelligibility, (ab)normality, and (un)certainty by which these tools operate and that this process is oriented toward the production of commercially actionable information.
Does AI Debias Recruitment? Race, Gender, and AI's "Eradication of Difference"
In: Philosophy & technology, Band 35, Heft 4
ISSN: 2210-5441
AbstractIn this paper, we analyze two key claims offered by recruitment AI companies in relation to the development and deployment of AI-powered HR tools: (1) recruitment AI can objectively assess candidates by removing gender and race from their systems, and (2) this removal of gender and race will make recruitment fairer, help customers attain their DEI goals, and lay the foundations for a truly meritocratic culture to thrive within an organization. We argue that these claims are misleading for four reasons: First, attempts to "strip" gender and race from AI systems often misunderstand what gender and race are, casting them as isolatable attributes rather than broader systems of power. Second, the attempted outsourcing of "diversity work" to AI-powered hiring tools may unintentionally entrench cultures of inequality and discrimination by failing to address the systemic problems within organizations. Third, AI hiring tools' supposedly neutral assessment of candidates' traits belie the power relationship between the observer and the observed. Specifically, the racialized history of character analysis and its associated processes of classification and categorization play into longer histories of taxonomical sorting and reflect the current demands and desires of the job market, even when not explicitly conducted along the lines of gender and race. Fourth, recruitment AI tools help produce the "ideal candidate" that they supposedly identify through by constructing associations between words and people's bodies. From these four conclusions outlined above, we offer three key recommendations to AI HR firms, their customers, and policy makers going forward.
Utopia/Dystopia, Race, Gender, and New Forms of Humanism in Women's Science Fiction
This thesis aims to uncover new forms of humanism grounded in a critique of systems that produce and reify race and gender by staging a conversation between six contemporary works of science fiction (SF) written by women from Italy, France, Spain, and the UK, and five acclaimed theorists in the fields of gender, queer, postcolonial, humanist, and cultural studies: Judith Butler, Rosi Braidotti, Gayatri Spivak, Paul Gilroy, and Jack Halberstam. As outlined in the second chapter, I focus, in particular, on Butler's conception of subjects who 'become' through affective encounters, Braidotti's critical posthumanism, Spivak and Gilroy's respective notions of 'planetarity,' and Halberstam's theory of a 'queer art of failure.' In doing so, this thesis asserts the complementarity of academic and science fictional enquiries into what I view as examples of new forms of humanism that arise from historicised interrogations of systems of race and gender. The first chapter introduces the way in which SF appeals to women writers who embrace the genre's political energy and its anti-racist, anti-sexist, and humanistic potential by tracing a genealogy of European women's SF from the seventeenth century to the present day. The second half of the thesis reads examples of politically charged SF from my corpus alongside the critical theory outlined in the second chapter, in order to demonstrate how SF engages with new forms of humanism through a critique and reformulation of issues of race and gender. I follow this analysis with an exploration of the way in which SF's unique spatial attributes can probe the borders of the planetary humanisms or 'planetarity' proposed by Gilroy and Spivak. I finally assess, by way of a conclusion, the extent to which SF can reassemble and amplify the achievements of these new forms of anti-racist and anti-sexist humanism.
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Feminist AI: critical perspectives on data, algorithms and intelligent machines
"Feminist AI: Critical Perspectives on Data, Algorithms and Intelligent Machines is the first volume to bring together leading feminist thinkers from across the disciplines to explore the impact of artificial intelligence (AI) and related data-driven technologies on human society. Recent years have seen both an explosion in AI systems and a corresponding rise in important critical analyses of these technologies. Central to these analyses has been feminist scholarship, which calls upon the AI sector to be accountable for designing and deploying AI in ways that further, rather than undermine, the pursuit of social justice. Feminist AI showcases the vital contributions of feminist scholarship to thinking about AI, data, and intelligent machines as well as laying the groundwork for future feminist scholarship on AI. It brings together scholars from a variety of disciplinary backgrounds, from computer science, software engineering, and medical sciences to political theory, anthropology, and literature. It provides an entry point for scholars of AI, science and technology into the diversity of feminist approaches to AI, and creates a rich dialogue between scholars and practitioners of AI to examine the powerful congruences and generative tensions between different feminist approaches to new and emerging technologies"--